Computer Sciences Commons^™

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

Accountability Responsibility As An Instrument For Performance Measurement, Burhan Rexhepi B.R

International Journal of Business and Technology

This paper addresses the role and importance of accounting information, in particular liability accounting and the impact of liability centers on the success of the enterprise. The success of business decision making is closely linked to the quality and accuracy of accounting information. Every entity, regardless of ownership, size and form of legal organization, the capital structure exists and functions to achieve its objectives.

We live in a time of great changes in external environmental factors, which impose the need to know modern methods and models for running a business. However, the main basis of business success depends on the …

Types Of Financial And Economic Crisis, Burhan R. Rexhepi B.R

International Journal of Business and Technology

Financial crises have caused much debate among different economists. They have attempted to explore any possibility of detecting and preventing crises before they cause the damages that will require way more time and energy to repair the situation and bring the economies back on the right track of sustainable development. The purpose of this study is to analyze different types of financial crises that have affected the economies of the world in order to draw lessons from their experiences. Analysis of this study is divided into four types of financial crises: Banking crisis, speculative bubbles and the market failures, international …

An Outlook Of Factoring Industry In The World And In Kosovo, Burhan R. Rexhepi B.R

International Journal of Business and Technology

Factoring is the most appropriate one for both bank and SMEs as it is considering a method of raising short- term working capital for enterprise by exchanging its A/R, not collateral focused and not adding any liability into their balance sheet. Moreover, factoring is a comprehensive financial service that includes not only financing but also credit protection, accounts receivable bookkeeping and collection services. Factoring not only brings benefit to CBs as a new service for diversification and increasing turnover but also supports SMEs to access financing for roll-up their business and gaining profit from achieving advantages of competitiveness. Although it …

A Novel Multi-Model Patient Similarity Network Driven By Federated Data Quality And Resource Profiling, Alramzana Nujum Navaz

Thesis/ Dissertation Defenses

Smart and Connected Health (SCH) is revolutionizing healthcare by leveraging extensive healthcare data for precise, personalized medicine. At its core, SCH relies on the concept of patient similarity, which involves the comparative analysis of newly encountered patients with those who exhibit comparable similarities from the existing patient cohort. Yet, this approach faces significant challenges, including data heterogeneity and dimensionality. Our research introduces a multi-dimensional Patient Similarity Network (PSN) Fusion model tailored to handle both static and dynamic features. The static data analysis focuses on extracting contextual information using Bidirectional Encoder Representations from Transformers (BERT), while dynamic features are captured through …

Automation Of Crack Detection And Quantification In Civil Infrastructure Facilities Using Deep Learning Techniques, Luqman Ali

Thesis/ Dissertation Defenses

Cracks are the earliest signs of structural deterioration that reduce the lifespan and reliability of structures and can lead to severe damage. Assessment and monitoring of the facilities are required for lifetime maintenance and failure prediction. Structure condition information can be obtained manually, i.e., through subjective visual inspection and evaluation by human experts. Manual inspection techniques are labor-intensive, time-consuming, and inspector-dependent, i.e., vulnerable to the inspector’s perceptiveness. Automatic crack detection is crucial at the earliest stage to avoid further structure degradation and allow fast intervention. Deep Learning algorithms have become more popular in crack detection systems in recent years. However, …

Uavs And Deep Neural Networks: An Alternative Approach To Monitoring Waterfowl At The Site Level, Zachary J. Loken

LSU Master's Theses

Understanding how waterfowl respond to habitat restoration and management activities is crucial for evaluating and refining conservation delivery programs. However, site-specific waterfowl monitoring is challenging, especially in heavily forested systems such as the Mississippi Alluvial Valley (MAV)—a primary wintering region for ducks in North America. I hypothesized that using uncrewed aerial vehicles (UAVs) coupled with deep learning-based methods for object detection would provide an efficient and effective means for surveying non-breeding waterfowl on difficult-to-access restored wetland sites. Accordingly, during the winters of 2021 and 2022, I surveyed wetland restoration easements in the MAV using a UAV equipped with a dual …

An Overview Of Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Complex Systems Faculty Publications and Presentations

A talk on my book, Elements and Relations: Aspects of a Scientific Metaphysics. Book description:

This book develops the core proposition that systems theory is an attempt to construct an “exact and scientific metaphysics,” a system of general ideas central to science that can be expressed mathematically. Collectively, these ideas would constitute a non-reductionist “theory of everything” unlike what is being sought in physics. Inherently transdisciplinary, systems theory offers ideas and methods that are relevant to all of the sciences and also to professional fields such as systems engineering, public policy, business, and social work. To demonstrate the generality …

All Quiet On The Digital Front: The Unseen Psychological Impacts On Cybersecurity First Responders, Tammie R. Hollis

USF Tampa Graduate Theses and Dissertations

Driven by the increasing frequency of cyberattacks and the existing talent gap between industry needs and skilled professionals, this research study focused on the crucial human element in the domain of cybersecurity incident response. The objective of this dissertation was to offer a meaningful exploration of the lived experiences encountered by cybersecurity incident responders and an assessment of the subsequent impacts on their well-being. Additionally, this study sought to draw comparisons between the experiences of cybersecurity incident responders and their counterparts in traditional emergency response roles. Semi-structured interviews were conducted with a cohort of 22 individuals with first-hand experience working …

Large Language Model Use Cases For Instruction, Plus A Primer On Prompt Engineering, Roy Haggerty, Justin Cochran

LSU Health New Orleans Symposium Series on Artificial Intelligence

AMA Credit Designation Statement: The Louisiana State University School of Medicine, New Orleans designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

NCPD Credit Designation Statement: Nursing participants may earn 1.0 NCPD contact hours. Each nursing participant must be present for the entire session for which NCPD contact hours are requested and must complete an evaluation of the session to receive credit.

The Fast And The Curious: Accelerating Literature Reviews With Ai, Jennifer Freer, Natalia Tingle Dolan, Gabrielle Wiersma

Presentations and other scholarship

As the world of academic research shifts gears into the digital age, AI-powered tools are beginning to shape the scholarly landscape. Just as high-performance vehicles transformed the world of car racing, AI-powered tools like scite, Elicit, and Research Rabbit have the potential to revolutionize the traditional literature review process. This presentation will accelerate your understanding of AI literature review tools and how these technologies can turbocharge the research process. Navigating between traditional library tools and AI-powered systems can be like choosing the right vehicle for the race. AI tools can enhance the speed, depth, and breadth of literature reviews, allowing …

Machine Learning For Electronic Design Automation: Specification Mining And High-Level Synthesis, Md Rubel Ahmed

USF Tampa Graduate Theses and Dissertations

The rapid growth of complex system-on-chip (SoC) designs has presented unprecedented opportunities and challenges in electronic design automation (EDA). This dissertation explores two facets of electronic design automation: message flow specification mining using data mining and natural language processing (NLP) and high-level synthesis (HLS) acceleration using different machine learning (ML) methods. It also discusses an ML model co-optimization method for energy-efficient hardware implementation.

Effective SoC design validation relies heavily on message flow specifications. This dissertation presents an efficient technique for synthesizing finite state automaton (FSA) models from SoC execution traces. The synthesized models can provide valuable insights into the on-chip …

Refining The Machine Learning Pipeline For Us-Based Public Transit Systems, Jennifer Adorno

USF Tampa Graduate Theses and Dissertations

According to the Population Division of the United Nations, in the United States, almost 90% of the population will live in urban areas by the year 2050. As the population in a given area increases, higher traffic congestion follows due to an increase of vehicles in the road. A possible way to alleviate congestion could be with widespread use of public transit. However, according to the US Census Bureau, the percentage of individuals commuting through public transportation has been decreasing steadily over time, and the American Community Survey reports that during 2019, only around five percent of the US population …

Big Data Analytics For Healthcare Social Media: New Algorithms And Insights, Negar Maleki

USF Tampa Graduate Theses and Dissertations

Over the last two decades, there has been a rapid evolution in information and communication technology, including the emergence of social media. Social media has a significant impact on various fields such as politics, business, culture, education, careers, innovation, and especially healthcare. This influence is not a new phenomenon since a survey from ten years ago showed that up to 78\% of American adults used the internet to look for health-related information for themselves or someone else. With the shift towards on-demand services in society, healthcare is also affected by this trend. Instead of waiting for weeks or months to …

A Data-Efficient Approach For Effective Diagnosis Of Left Ventricular Hypertrophy From Echocardiography Modality, Moomal Farhad Farhad

Thesis/ Dissertation Defenses

Left Ventricular Hypertrophy (LVH) is a medical condition characterized by the thickening and enlargement of the left ventricle (LV) of the heart. Accurate and timely diagnosis of LVH is vital for clinical prognosis and treatment decisions. Echocardiography has emerged as the gold standard for diagnosing LVH due to its ability to independently predict long-term risks such as heart failure and stroke. Echocardiography, a non-invasive and cost-effective imaging technology, is instrumental in assessing various aspects of heart health. Among the critical diagnostic calculations made possible by echocardiography, the determination of ejection fraction and heart chamber size is paramount in assessing LVH. …

Foundation Of The Superhypersoft Set And The Fuzzy Extension Superhypersoft Set: A New Vision, Florentin Smarandache

Neutrosophic Systems with Applications

We introduce for the first time the SuperHyperSoft Set and the Fuzzy and Fuzzy Extension SuperHyperSoft Set. Through a theorem, we prove that the SuperHyperSoft Set is composed from many HyperSoft Sets.

Human Vs Machine: Hyper-Realistic Avatars And Their Efficacy As A Communication Channel, Jill S. Schiefelbein

USF Tampa Graduate Theses and Dissertations

Hyper-realistic avatars (HRAs), a form of synthetic media, are custom-created digital embodiments of a human, created by capturing and combining that person’s video and vocal likeness. This is the first known study of the efficacy of videos delivered by hyper-realistic avatars as a communication channel in comparison to videos delivered by their human counterparts. An experiment testing how information retention, engagement, and trust vary between viewers of videos delivered by a real human, videos delivered by the HRA representing that same human, and videos delivered by the HRA that discloses to viewers that it is a hyper-realistic avatar is presented. …

Modelling Prediction Of Cities Real Estate Price Trend Using Recurrent Neural Network: A Case Of Dar Es Salaam City, Ellen Kalinga

Tanzania Journal of Engineering and Technology (TJET)

Real estate refers to a class of real property such as land and its associated infrastructure. The prediction of real estate prices in cities, which is affected by a number of parameters, is an open research problem. The lack of reliable and effective tools for price forecasting in real estate, especially in residential housing, can adversely affect investment flows and the growth of the real estate sector. Taking Tanzania as an example, the price prediction practices rely on human suggestions that are prone to personal bias and subjective to price hysteria for personal gain and impact consumer expectations. To address …

Foundation Of The Superhypersoft Set And The Fuzzy Extension Superhypersoft Set: A New Vision, Florentin Smarandache

Neutrosophic Systems with Applications

We introduce for the first time the SuperHyperSoft Set and the Fuzzy and Fuzzy Extension SuperHyperSoft Set. Through a theorem, we prove that the SuperHyperSoft Set is composed from many HyperSoft Sets.

Preface: Special Issue On Nlp Approaches To Offensive Content Online, Marcos Zampieri, Isabelle Augenstein, Siddharth Krishnan, Joshua Melton, Preslav Nakov

Natural Language Processing Faculty Publications

No abstract provided.

Integrating Embeddings From Multiple Protein Language Models To Improve Protein O-Glcnac Site Prediction, Suresh Pokharel, Pawel Pratyush, Hamid D. Ismail, Junfeng Ma, Dukka Kc

Michigan Tech Publications

O-linked β-N-acetylglucosamine (O-GlcNAc) is a distinct monosaccharide modification of serine (S) or threonine (T) residues of nucleocytoplasmic and mitochondrial proteins. O-GlcNAc modification (i.e., O-GlcNAcylation) is involved in the regulation of diverse cellular processes, including transcription, epigenetic modifications, and cell signaling. Despite the great progress in experimentally mapping O-GlcNAc sites, there is an unmet need to develop robust prediction tools that can effectively locate the presence of O-GlcNAc sites in protein sequences of interest. In this work, we performed a comprehensive evaluation of a framework for prediction of protein O-GlcNAc sites using embeddings from pre-trained protein language models. In particular, we …

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Application Of Physics Informed Neural Networks For Predicting Disease Dynamics, Alonso Gabriel Ogueda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Deciphering Trends And Tactics: Data-Driven Techniques For Forecasting Information Spread And Detecting Coordinated Campaigns In Social Media, Kin Wai Ng Lugo

USF Tampa Graduate Theses and Dissertations

The main objective of this dissertation is to develop models that predict and investigate the spread of information in social media over time. In this context, we consider topics of discussions as the information that spreads. Thus, we are interested in forecasting the number of messages per day in a future interval of time. We take a data-driven approach, in which we compare our results with real datasets from a multitude of socio-political contexts and from multiple social media platforms, specifically, Twitter and YouTube.

We identified a number of challenges related to forecasting social media time series per topic. First, …

Bridging Domain Gaps For Cross-Spectrum And Long-Range Face Recognition Using Domain Adaptive Machine Learning, Cedric Armel Nimpa Fondje

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Face recognition technology has witnessed significant advancements in recent decades, enabling its widespread adoption in various applications such as security, surveillance, and biometrics applications. However, one of the primary challenges faced by existing face recognition systems is their limited performance when presented with images from different modalities or domains( such as infrared to visible, long range to close range, nighttime to daytime, profile to f rontal, etc.) Additionally, advancements in camera sensors, analytics beyond the visible spectrum, and the increasing size of cross-modal datasets have led to a particular interest in cross-modal learning for face recognition in the biometrics and …

Disease Informed Neural Network And Mathematical Modeling Of Covid-19 With Human Intervention, Jeremis Morales-Morales, Alonso Gabriel Ogueda, Carmen Caiseda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Green Synthesized Silver Nanoparticles-Based Sensing For Monitoring Water Pollution: An Updated Review, Muhamad Allan Serunting, Muhammad Ali Zulfikar, Henry Setiyanto, Dian Ayu Setyorini, Vienna Saraswaty

Karbala International Journal of Modern Science

Water is a basic human need and has been heavily contaminated. Therefore, it becomes a concern to remove the pollutant and monitor its quality. The removal methods include precipitation, filtration, adsorption, and photodegradation. Meanwhile, the monitoring can be done by measuring and analyzing the contaminant using spectrophotometry and chromatography. Nevertheless, those methods usually need a complicated preparation, and are expensive. Thus, a simple method is necessary to overcome these drawbacks by developing a sensor. In recent years, the sensor performance has been enhanced by using nanomaterials, such as silver nanoparticles (AgNPs). AgNPs can be synthesized using plant extracts through a …

Synthesis And Characterization Of Zirconium Oxide Nanoparticles Using Z. Officinale And S. Aromaticum Plant Extracts For Antibacterial Application, M. J. Tuama, M. F. A. Alias

Karbala International Journal of Modern Science

Abstract The dramatic rise in bacterial infections and increased resistance to conventional antibiotics has led to the exploration of biologically derived nanomaterials to counteract bacterial activity. Nanotechnology, which deals with materials at the atomic or molecular level, is a promising way to achieve this goal. Zirconium oxide nanoparticles (ZrO2NPs) have shown strong antibacterial effects due to the increased surface-to-volume ratio at the nanoscale. This study focused on the production of ZrO2NPs in an environmentally friendly manner, which included extracts from Zingiber officinale (ginger), where G-ZrO2NPs were produced, and Syzygium aromaticum (clove), which produced S-ZrO2NPs. Various techniques were used, such as …

Smart Street Light Control: A Review On Methods, Innovations, And Extended Applications, Fouad Agramelal, Mohamed Sadik, Youssef Moubarak, Saad Abouzahir

Computer Vision Faculty Publications

As urbanization increases, streetlights have become significant consumers of electrical power, making it imperative to develop effective control methods for sustainability. This paper offers a comprehensive review on control methods of smart streetlight systems, setting itself apart by introducing a novel light scheme framework that provides a structured classification of various light control patterns, thus filling an existing gap in the literature. Unlike previous studies, this work dives into the technical specifics of individual research papers and methodologies, ranging from basic to advanced control methods like computer vision and deep learning, while also assessing the energy consumption associated with each …